---
language:
- en
- fr
- de
- es
- pt
- it
- nl
- pl
- cs
- uk
- sv
- ro
- hu
- el
- da
- nb
- sk
- fi
- bg
- ru
- ca
- lt
- lv
- sl
- hr
- sr
- mk
- bs
- be
- gl
- eu
- nn
- is
- cy
- mt
- lb
- ga
- ast
- fo
- gd
- oc
license: cc0-1.0
task_categories:
- text-generation
- fill-mask
pretty_name: "European HPLT v1 — 45M docs, 41 languages"
size_categories:
- 10M<n<100M
source_datasets:
- hplt-project/hplt_monolingual_v3
tags:
- european
- multilingual
- pretraining
- hplt
---

# European HPLT v1

A multilingual pretraining corpus of **45,031,396 documents** (~50.9B estimated tokens, ~190 GB raw JSONL) across **41 European languages**, built from [HPLT Monolingual v3](https://hplt-project.org/datasets/v3) high-quality web crawl data.

The corpus spans Germanic, Romance, Slavic, Celtic, Baltic, Finno-Ugric, Greek, and other European language families. Every document has an HPLT WDS quality score of 10 or higher (the top of the quality distribution).

## Quick Start

```python
from datasets import load_dataset

# Streaming (recommended — corpus is ~190 GB)
ds = load_dataset("ashtok897/european-hplt-v1", split="train", streaming=True)
for row in ds.take(3):
    print(row["lang"], row["text"][:100])

# Filter by language
de_ds = ds.filter(lambda x: x["lang"] == "de")

# Full training split (requires disk space)
ds = load_dataset("ashtok897/european-hplt-v1", split="train")
```

## Language Distribution

| Language | BCP-47 | Documents | % | Est. Tokens | Avg Words/Doc |
|---|---|---:|---:|---:|---:|
| English | `en` | 3,080,434 | 6.84% | ~4.44B | 955 |
| French | `fr` | 2,726,717 | 6.06% | ~4.56B | 1,073 |
| German | `de` | 2,723,089 | 6.05% | ~5.23B | 1,051 |
| Spanish | `es` | 2,463,158 | 5.47% | ~2.91B | 768 |
| Portuguese | `pt` | 2,171,285 | 4.82% | ~2.46B | 728 |
| Italian | `it` | 2,168,007 | 4.81% | ~2.88B | 820 |
| Dutch | `nl` | 1,902,030 | 4.22% | ~1.64B | 538 |
| Polish | `pl` | 1,891,358 | 4.20% | ~1.98B | 591 |
| Czech | `cs` | 1,600,788 | 3.55% | ~1.34B | 516 |
| Ukrainian | `uk` | 1,577,030 | 3.50% | ~1.08B | 381 |
| Swedish | `sv` | 1,362,129 | 3.02% | ~1.58B | 721 |
| Romanian | `ro` | 1,329,418 | 2.95% | ~1.29B | 617 |
| Hungarian | `hu` | 1,328,026 | 2.95% | ~1.36B | 555 |
| Greek | `el` | 1,322,934 | 2.94% | ~1.41B | 639 |
| Danish | `da` | 1,085,979 | 2.41% | ~1.16B | 668 |
| Norwegian Bokmål | `nb` | 1,081,349 | 2.40% | ~0.99B | 586 |
| Slovak | `sk` | 1,063,235 | 2.36% | ~0.72B | 413 |
| Finnish | `fi` | 1,062,298 | 2.36% | ~1.64B | 751 |
| Bulgarian | `bg` | 1,060,225 | 2.35% | ~0.73B | 434 |
| Russian | `ru` | 1,046,533 | 2.32% | ~3.62B | 1,847 |
| Catalan | `ca` | 792,769 | 1.76% | ~0.60B | 499 |
| Lithuanian | `lt` | 792,614 | 1.76% | ~0.52B | 352 |
| Latvian | `lv` | 784,033 | 1.74% | ~0.55B | 391 |
| Slovenian | `sl` | 783,987 | 1.74% | ~0.57B | 449 |
| Croatian | `hr` | 771,689 | 1.71% | ~0.56B | 448 |
| Serbian | `sr` | 759,832 | 1.69% | ~0.54B | 440 |
| Macedonian | `mk` | 648,038 | 1.44% | ~0.34B | 333 |
| Bosnian | `bs` | 642,025 | 1.43% | ~0.44B | 427 |
| Belarusian | `be` | 639,982 | 1.42% | ~0.38B | 337 |
| Galician | `gl` | 639,327 | 1.42% | ~0.42B | 424 |
| Basque | `eu` | 636,441 | 1.41% | ~0.36B | 294 |
| Norwegian Nynorsk | `nn` | 535,072 | 1.19% | ~0.36B | 437 |
| Icelandic | `is` | 432,802 | 0.96% | ~0.82B | 1,073 |
| Welsh | `cy` | 431,246 | 0.96% | ~0.25B | 390 |
| Maltese | `mt` | 326,736 | 0.73% | ~0.21B | 358 |
| Luxembourgish | `lb` | 324,914 | 0.72% | ~0.22B | 417 |
| Irish | `ga` | 321,842 | 0.71% | ~0.21B | 431 |
| Asturian | `ast` | 215,942 | 0.48% | ~0.19B | 555 |
| Faroese | `fo` | 209,925 | 0.47% | ~0.10B | 292 |
| Scottish Gaelic | `gd` | 197,604 | 0.44% | ~0.15B | 502 |
| Occitan | `oc` | 98,554 | 0.22% | ~0.08B | 530 |
| **Total** | | **45,031,396** | **100%** | **~50.88B** | **681** |

> Token estimates use chars÷4. Actual count varies by tokenizer.

### Notable observations

- **Russian** has the highest average doc length (1,847 words) — Russian web articles in HPLT v3 tend to be substantially longer than other languages.
- **Icelandic** has unusually long average doc length (1,073 words) for its size tier, similar to Tier 1 languages.
- **German** has the highest total token share among Latin-script languages (~5.23B) despite ranking 3rd by doc count.
- **Estonian** (`et` / `est_Latn`) was targeted but is **not present in HPLT v3 sorted collection** and was excluded.

## Dataset Fields

| Field | Type | Description |
|---|---|---|
| `text` | string | Document text |
| `lang` | string | BCP-47 language code |
| `url` | string | Source URL |
| `score` | float | HPLT WDS quality score (raw integer, higher = better; all docs ≥ 10) |
| `collection` | string | Source MIME type (e.g. `text/html`) |
| `web-register` | string | Document register/genre code (see Web Registers section) |
| `prob` | float | Language detection confidence |
| `char_count` | int | Character count |
| `word_count` | int | Whitespace-split word count |
| `doc_id` | string | Unique per-language ID, e.g. `de_0000001` |

## Data Splits

Split ratios are 98% / 1% / 1% over Parquet shards (250,000 rows per shard, ~180 shards total).

| Split | Documents | Shards |
|---|---:|---:|
| train | ~44.13M | ~176 |
| validation | ~450K | ~2 |
| test | ~450K | ~2 |

### Note on Data Completeness

One shard (`train-00107-of-00181.parquet`) was removed from the published train
split because Hugging Face's ClamAV scanner flagged a false-positive malware
signature (`Email.Trojan.Trojan-939`) on email-like text within the crawled web
content. Parquet files contain only data and cannot execute code — the flag was
a byte-pattern match against text in the `text` column, not executable malware.
As a result, the train split contains 176 shards (~44.0M documents) rather than
177. Remaining file names keep their original `of-00181` suffix for consistency;
the `datasets` loader globs all available shards, so this does not affect loading.

## How It Was Built

**Source:** HPLT v3 sorted shards (`https://data.hplt-project.org/three/sorted`), which order documents by WDS quality score descending — every document in this corpus has a WDS score of 10 or higher.

**Quality filtering** (applied inline during download):
- 50–100,000 characters per document
- Max 50% non-alphabetic characters (Unicode-aware)
- Min average word length 2.0 characters

**Deduplication:**
- Exact SHA-256 hash dedup on all languages
- MinHash near-duplicate removal **disabled** for this release — HPLT v3 already applies global near-deduplication, so re-running MinHash on Indo-European languages adds significant compute for marginal gain. May be re-enabled in a future release.

**Merge:** Languages are interleaved according to configured fractions targeting a balanced multilingual corpus. The `merge.py` step uses an adaptive quota algorithm that:
- Caps each language at its available document count
- Auto-excludes languages with less than 10% of their target quota (none were excluded in this release except Estonian, which had 0 data)
- Redistributes excluded quota across the remaining languages
- Shuffles the final output (deterministic, seed=42)

**Pipeline code:** [github.com/ashtok/build-multilingual-corpus](https://github.com/ashtok/build-multilingual-corpus)

## Web Register Distribution

HPLT v3 labels documents with a register/genre code:

| Register | Count | % | Meaning |
|---|---:|---:|---|
| IP | 14,245,000 | 31.6% | Informational persuasion |
| NA | 10,847,574 | 24.1% | Narrative |
| IN | 8,232,732 | 18.3% | Informational description |
| MT | 3,810,850 | 8.5% | Machine-translated |
| ID | 1,926,908 | 4.3% | Interactive discussion |
| OP | 1,823,791 | 4.1% | Opinion |
| HI | 1,220,284 | 2.7% | How-to / instructional |
| unknown | 1,176,071 | 2.6% | Unclassified |
| LY | 233,724 | 0.5% | Lyrical |

> To exclude machine-translated content, filter on `web-register != "MT"` (drops ~8.5%).

## Source Collection Types

| Collection | Count |
|---|---:|
| `text/html` | 44,927,249 |
| `application/atom+xml` | 46,512 |
| `application/xml` | 22,690 |
| (empty) | 16,567 |
| `application/xhtml+xml` | 6,492 |
| `application/vnd.oasis.opendocument.text` | 2,708 |
| `application/vnd.openxmlformats-officedocument.spreadsheetml.sheet` | 2,643 |
| `text/plain` | 1,771 |
| `application/rss+xml` | 1,700 |
| `application/epub+zip` | 1,407 |

99.8% of documents are HTML.

## Corpus Statistics Summary

| Metric | Value |
|---|---:|
| Total documents | 45,031,396 |
| Total characters | 203.5B |
| Total words | 30.7B |
| Estimated tokens | ~50.9B |
| Avg doc length (words) | 681 |
| Median doc length (words) | 264 |
| Min doc length (words) | 6 |
| Max doc length (words) | 26,373 |

## Limitations

- **Web text only** — no books, Wikipedia, or structured data
- **~8.5% machine-translated content** — identifiable via `web-register: MT`
- **No Estonian** — language unavailable in HPLT v3 sorted collection at corpus build time
- **No MinHash near-dedup** — exact dedup only (HPLT v3 already applies global near-dedup)
- **Tier-6 languages are data-limited** — Occitan, Scottish Gaelic, Faroese, Asturian have <250K docs each
- **Russian has only 1.05M docs** — substantially less than other Tier-1 languages because HPLT v3 sorted shards exhausted at this quality level
- **No PII filtering beyond HPLT defaults**
- **Language proportions are partially balanced, not natural** — high-resource languages are slightly down-weighted versus their raw web share to give more space to mid/low-resource languages

## Comparison with Related Corpora

| Corpus | Docs | Languages | Quality bar | Source |
|---|---:|---:|---|---|
| **European HPLT v1** | **45.0M** | **41** | WDS ≥ 10 | HPLT v3 |
| HPLT v3 (raw) | ~21B | 191 | None | HPLT v3 |
| CulturaX | 6.3T tokens | 167 | Heuristic | mC4 + OSCAR |
| RedPajama-v2 | 30T tokens | 5 | Quality signals | Common Crawl |
| OSCAR 23.01 | ~9.8B | 151 | None | Common Crawl |

This corpus trades scale for quality: every document is pre-filtered to the top WDS tier and the language mix is tilted to include lower-resource European languages that are underrepresented in other multilingual corpora.

## Citation

```bibtex
@dataset{europeanHPLTv1_2026,
  author    = {Mahajan, Ashutosh},
  title     = {European {HPLT} v1: A 45M-document Multilingual Corpus for 41 European Languages},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/ashtok897/european-hplt-v1}
}

@article{oepen2025hplt,
  title   = {{HPLT} 3.0: Very Large-Scale Multilingual Resources for {LLM} and {MT}},
  author  = {Oepen, Stephan and others},
  journal = {arXiv preprint arXiv:2511.01066},
  year    = {2025}
}
```

## License

[CC0 1.0 Universal](https://creativecommons.org/publicdomain/zero/1.0/) — inherited from HPLT v3.